README.md

metadata

license: apache-2.0
base_model: Qwen/Qwen3-Coder-30B-A3B-Instruct
tags:
  - angular
  - lora
  - peft
library_name: peft

angular-coder-30b-a3b-lora

The PEFT LoRA adapter behind bharathmuppa/angular-coder-30b-a3b. Apply it to Qwen/Qwen3-Coder-30B-A3B-Instruct:

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = "Qwen/Qwen3-Coder-30B-A3B-Instruct"
tok = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, dtype="auto", device_map="auto")
model = PeftModel.from_pretrained(model, "bharathmuppa/angular-coder-30b-a3b-lora")

Rank 16, alpha 16, dropout 0.05, target modules: q/k/v/o projections of every layer. Trained 796 optimizer steps (2.0 epochs), final eval loss 1.1662. train_summary.json in this repo holds the run settings. See the merged model card for data and training details.